Power control for partial channel-state information (CSI) multiple-input, multiple-output (MIMO) systems

ABSTRACT

Techniques for controlling the transmit power for a number of data streams in a wireless multi-channel (e.g., MIMO) communication system. In one method, a number of received symbol streams are initially processed in accordance with a particular (e.g., CCMI, CCMI-SC, MMSE, or MMSE-SC) receiver processing technique to provide a number of detected data streams. The post-detection SNRs of the detected data streams are estimated, and each SNR that exceeds a setpoint is identified. This setpoint may correspond to (1) the SNR needed to achieve the maximum allowed spectral efficiency or (2) the target SNR needed to achieve a specified spectral efficiency. A new (or adjusted) transmit power for each detected data stream associated with a post-detection SNR that exceeds the setpoint is determined and used for the data stream. Different power control schemes are provided for different classes of receiver processing techniques with different characteristics.

BACKGROUND

[0001] 1. Field

[0002] The present invention relates generally to data communication,and more specifically to techniques for controlling transmit power inmulti-channel communication systems (e.g., multiple-input,multiple-output (MIMO) systems) that utilize partial channel-stateinformation (CSI).

[0003] 2. Background

[0004] In a wireless communication system, an RF modulated signal from atransmitter may reach a receiver via a number of propagation paths. Thecharacteristics of the propagation paths typically vary over time due toa number of factors such as fading and multipath. To provide diversityagainst deleterious path effects and improve performance, multipletransmit and receive antennas may be used. If the propagation pathsbetween the transmit and receive antennas are linearly independent(i.e., a transmission on one path is not formed as a linear combinationof the transmissions on other paths), which is generally true to atleast an extent, then the likelihood of correctly receiving a datatransmission increases as the number of antennas increases. Generally,diversity increases and performance improves as the number of transmitand receive antennas increases.

[0005] A multiple-input, multiple-output (MIMO) communication systememploys multiple (N_(T)) transmit antennas and multiple (N_(R)) receiveantennas for data transmission. A MIMO channel formed by the N_(T)transmit and N_(R) receive antennas may be decomposed into N_(S)independent channels, with N_(S)≦min {N_(T), N_(R)}. Each of the N_(S)independent channels is also referred to as a spatial subchannel (or atransmission channel) of the MIMO channel and corresponds to adimension. The MIMO system can provide improved performance (e.g.,increased transmission capacity) if the additional dimensionalitiescreated by the multiple transmit and receive antennas are utilized. Forexample, an independent data stream may be transmitted on each of theN_(S) spatial subchannels to increase system throughput.

[0006] Multiple data streams may be transmitted on the spatialsubchannels using channel-state information (CSI), which is descriptiveof the characteristics of the MIMO channel. CSI may be categorized aseither “full CSI” or “partial CSI”. Full CSI includes sufficientcharacterization (e.g., amplitude and phase) of the propagation pathbetween each transmit-receive antenna pair in a (N_(R)×N_(T)) MIMOmatrix. Full CSI may not be available or practical for many MIMOsystems. Partial CSI may comprise, for example, thesignal-to-noise-and-interference ratios (SNRs) of the spatialsubchannels, which may be estimated by detecting the data streams and/orpilots transmitted on these subchannels. Each data stream may then becoded and modulated in accordance with a particular coding andmodulation scheme selected based on the subchannel's SNR.

[0007] The spatial subchannels of a MIMO system may experience differentchannel conditions (e.g., different fading and multipath effects) andmay achieve different SNRs for a given amount of transmit power.Consequently, the data rates that may be supported by the spatialsubchannels may be different from subchannel to subchannel. Moreover,the channel conditions typically vary with time. As a result, the datarates supported by the spatial subchannels also vary with time.

[0008] A key challenge in a MIMO system is the determination of thetransmit powers to use for the data transmissions on the spatialsubchannels based on the channel conditions. The goal of this transmitpower control should be to maximize spectral efficiency while meetingother system objectives, such as achieving a particular target frameerror rate (FER) for each data stream, minimizing interference, and soon.

[0009] In a practical communication system, there may be an upper limiton the data rate that may be used for any given data stream. Forexample, a set of discrete data rates may be supported by the system,and the maximum data rate from among these discrete data rates may beconsidered as the maximum spectral efficiency for any given data stream.In such a system, utilizing more transmit power than necessary for eachdata stream to achieve the target FER at the maximum data rate wouldresult in an ineffective use of the additional transmit power. Eventhough the excess transmit power may result in a lower FER, thisimprovement in FER may not be considered substantial since the targetFER has already been achieved. The excess transmit power for a givendata stream may result in additional interference to other data streams,which may then degrade the performance of these data streams.

[0010] There is therefore a need in the art for techniques to controlthe transmit power of the data streams in a MIMO system utilizingpartial CSI.

SUMMARY

[0011] Techniques are provided herein to control the transmit power fordata transmission in a MIMO system such that the desired spectralefficiency is obtained while minimizing the total required transmitpower. The post-detection SNRs of a number of data streams may beinitially estimated. The transmit power for each data stream is thendetermined by taking into account the specific receiver processingtechnique used to detect the data streams at the receiver. The newtransmit powers attempt to maintain the post-detection SNRs of the datastreams either (1) at the SNR, γ_(set), needed to achieve the maximumallowed spectral efficiency, for any SNR that exceeds γ_(set), or (2) ator near the target SNR needed for a specified spectral efficiency.

[0012] In a specific embodiment, a method is provided for controllingthe transmit power for a number of data streams in a wirelessmulti-channel (e.g., MIMO) communication system. Initially, a number ofreceived symbol streams are processed in accordance with a particularreceiver processing technique (e.g., a CCMI, CCMI-SC, MMSE, MMSE-SC, orsome other technique, as described below) to provide a number ofdetected data streams. The post-detection SNRs of the detected datastreams are estimated, and each SNR that exceeds a setpoint isidentified. This setpoint may correspond to the SNR needed to achievethe maximum allowed spectral efficiency (e.g., the maximum data ratesupported by the system) or the target SNR needed to achieve a specifiedspectral efficiency (e.g., a specific data rate). A new (or adjusted)transmit power for each detected data stream associated with apost-detection SNR that exceeds the setpoint is determined and used forthe data stream.

[0013] The post-detection SNRs of the data streams are dependent on thespecific receiver processing technique used at the receiver to detectthe data streams. Moreover, the relationships between transmit powersand post-detection SNRs for the detected data streams may or may not bedecorrelated. Different power control schemes are provided herein fordifferent classes of receiver processing techniques with differentcharacteristics. In a first class (which includes the CCMI and CCMI-SCtechniques), the detected data streams are decoupled by the receiverprocessing, and changing the transmit power of one data stream does notaffect the post-detection SNRs of the other data streams. The transmitpower for each detected data stream may then be determined withoutregards to the transmit powers for the other data streams. In a secondclass (which includes the MMSE and MMSE-SC techniques), thepost-detection SNR of a given data stream may be coupled to the transmitpowers of the other data streams, and a change in the transmit power forone data stream may affect the post-detection SNRs of the other datastreams. The transmit powers for the data streams may then be determinedin a manner to take into account this inter-dependency, and the poweradjustment may be iterated as many times as necessary to achieve thedesired results.

[0014] Various aspects and embodiments of the invention are described infurther detail below. The invention further provides methods,processors, receiver units, transmitter units, terminals, base stations,systems, and other apparatuses and elements that implement variousaspects, embodiments, and features of the invention, as described infurther detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The features, nature, and advantages of the present inventionwill become more apparent from the detailed description set forth belowwhen taken in conjunction with the drawings in which like referencecharacters identify correspondingly throughout and wherein:

[0016]FIG. 1 is a block diagram of an embodiment of a transmitter systemand a receiver system in a MIMO system;

[0017]FIG. 2 shows two plots for spectral efficiency versuspost-detection SNR;

[0018]FIG. 3 is a flow diagram of a process for adjusting the transmitpower to achieve a set of post-detection SNRs for a CCMI receiver;

[0019]FIG. 4 is a flow diagram illustrating the CCMI-SC receiverprocessing technique;

[0020]FIG. 5 is a flow diagram of a process for maximizing spectralefficiency while minimizing the total required transmit power for theCCMI-SC receiver;

[0021]FIG. 6 is a flow diagram of a process for adjusting the transmitpower to achieve a set of post-detection SNRs for an MMSE receiver;

[0022]FIG. 7 is a flow diagram of a process for adjusting the transmitpower to achieve a set of post-detection SNRs for an MMSE-SC receiver;

[0023]FIG. 8 shows a plot of spectral efficiency versus post-detectionSNR for a communication system that supports a set of discrete datarates;

[0024]FIGS. 9A and 9B are block diagrams of a RX MIMO/data processorthat respectively implements and does not implement the successivecancellation receiver processing technique; and

[0025]FIGS. 10A and 10B are block diagrams of two spatial processorsthat implement the CCMI and MMSE techniques, respectively.

DETAILED DESCRIPTION

[0026] The techniques described herein for controlling transmit powerfor data transmissions may be used for various multi-channelcommunication systems. Such multi-channel communication systems includemultiple-input, multiple-output (MIMO) communication systems, orthogonalfrequency division multiplexing (OFDM) communication systems, MIMOsystems that utilize OFDM (i.e., MIMO-OFDM systems), and others. Themulti-channel communication systems may also implement code divisionmultiple access (CDMA), time division multiple access (TDMA), frequencydivision multiple access (FDMA), or some other multiple accesstechniques. Multiple-access communication systems can support concurrentcommunication with a number of terminals (i.e., users). For clarity,various aspects and embodiments of the invention are describedspecifically for a MIMO system such as a multiple-antenna wirelesscommunication system.

[0027]FIG. 1 is a block diagram of an embodiment of a transmitter system110 and a receiver system 150 in a MIMO system 100.

[0028] At transmitter system 110, traffic data for a number of datastreams is provided from a data source 112 to a transmit (TX) dataprocessor 114. Each data stream may be transmitted over a singletransmission channel or a group of transmission channels. TX dataprocessor 114 formats, codes, and interleaves the traffic data for eachdata stream based on a particular coding scheme selected for that datastream to provide coded data. The coded traffic data for all datastreams may be multiplexed with pilot data (e.g., using time divisionmultiplex (TDM) or code division multiplex (CDM)) in all or a subset ofthe transmission channels to be used for data transmission. The pilotdata is typically a known data pattern that is processed in a knownmanner, if at all. The multiplexed pilot and coded traffic data for eachdata stream is then modulated (i.e., symbol mapped) based on aparticular modulation scheme (e.g., BPSK, QSPK, M-PSK, or M-QAM)selected for that data stream to provide modulation symbols. The datarate, coding, interleaving, and modulation for each data stream may bedetermined by controls provided by a controller 130.

[0029] The modulation symbols for all data streams are then provided toa TX MIMO processor 120. In an embodiment, TX MIMO processor 120 scalesthe modulation symbols for each data stream by a respective weightdetermined based on the amount of transmit power to be used for thatdata stream. TX MIMO processor 120 then demultiplexes the scaledmodulation symbols into (up to) N_(T) transmit symbol streams, onetransmit symbol stream for each of the (up to) N_(T) transmit antennasto be used for data transmission. The up to N_(T) transmit symbolstreams are then provided to transmitters (TMTR) 122 a through 122 t.

[0030] Each transmitter 122 for a selected transmit antenna receives andprocesses a respective transmit symbol stream. For an OFDM system, eachtransmitter transforms the scaled modulation symbols (e.g., using theinverse Fourier transform) to form OFDM symbols, and may further appenda cyclic prefix to each OFDM symbol to form a corresponding transmissionsymbol. Each transmitter converts the symbol stream into one or moreanalog signals and further conditions (e.g., amplifies, filters, andquadrature modulates) the analog signals to generate a modulated signalsuitable for transmission over the MIMO channel. Up to N_(T) modulatedsignals from transmitters 122 a through 122 t are then transmitted fromup to N_(T) antennas 124 a through 124 t, respectively.

[0031] At receiver system 150, the transmitted modulated signals arereceived by N_(R) antennas 152 a through 152 r, and the received signalfrom each antenna 152 is provided to a respective receiver (RCVR) 154.Each receiver 154 conditions (e.g., filters, amplifies, anddownconverts) the received signal and digitizes the conditioned signalto provide a respective stream of samples. Each sample stream mayfurther be processed (e.g., demodulated with a recovered pilot) toobtain a corresponding stream of received symbols.

[0032] An RX MIMO/data processor 160 then receives and processes theN_(R) received symbol streams to provide N_(S) “detected” data streams.RX MIMO/data processor 160 may perform spatial or space-time processingon the N_(R) received symbol streams using any of a number of spatialand space-time receiver processing techniques, some of which aredescribed in further detail below. Each detected data stream includessymbols that are estimates of the modulation symbols transmitted forthat data stream. RX MIMO/data processor 160 then demodulates,deinterleaves, and decodes each detected data stream to recover thetraffic data for the data stream. The processing by RX MIMO/dataprocessor 160 is complementary to that performed by TX MIMO processor120 and TX data processor 114 at transmitter system 110.

[0033] RX MIMO processor 160 may further derive an estimate of thesignal-to-noise-and-interference ratios (SNRs) of the data streams, andpossibly other channel characteristics, and provide these quantities toa controller 170. RX MIMO/data processor 160 may also provide the statusof each received frame or packet, one or more other performance metricsindicative of the decoded results, and possibly other information.Controller 170 collects channel state information (CSI), which maycomprise all or some of the information received from RX MIMO/dataprocessor 160. The CSI is then processed by a TX data processor 178,modulated by a modulator 180, conditioned by transmitters 154 a through154 r, and transmitted back to transmitter system 110.

[0034] At transmitter system 110, the modulated signals from receiversystem 150 are received by antennas 124, conditioned by receivers 122,demodulated by a demodulator 140, and processed by a RX data processor142 to recover the CSI reported by the receiver system. The CSI is thenprovided to controller 130 and used to generate various controls for TXdata processor 114 and TX MIMO processor 120.

[0035] Controllers 130 and 170 direct the operation at the transmitterand receiver systems, respectively. Memories 132 and 172 provide storagefor program codes and data used by controllers 130 and 170,respectively.

[0036] For a MIMO system that employs multiple (N_(T)) transmit antennasand multiple (N_(R)) receive antennas for data transmission, the MIMOchannel formed by the N_(T) transmit and N_(R) receive antennas may bedecomposed into N_(S) independent channels, with N_(S)≦min {N_(T),N_(R)}. Each of the N_(S) independent channels is also referred to as aspatial subchannel (or a transmission channel) of the MIMO channel. Thenumber of spatial subchannels is determined by the number of eigenmodesfor the MIMO channel, which in turn is dependent on a channel responsematrix, H, that describes the response between the N_(T) transmit andN_(R) receive antennas. The elements of the channel response matrix, H,are composed of independent Gaussian random variables, {h_(j,i)}, eachof which is descriptive of the coupling (i.e., the complex gain) betweenthe i-th transmit antenna and the j-th receive antenna

[0037] In general, each data stream may be transmitted from one ormultiple transmit antennas. However, for simplicity, much of thedescription below assumes that one data stream is transmitted from eachtransmit antenna. Each spatial subchannel may support one data stream.For simplicity, the number of spatial subchannels is assumed to be equalto the number of transmit antennas and receive antennas (i.e.,N_(S)=N_(T)=N_(R)).

[0038] The model for the MIMO system may be expressed as:

y=HAx+n,  Eq (1)

[0039] where

[0040] y is the received vector, i.e., y[y₁ y₂ . . . y_(N) _(R) ]^(T),where {y_(j)} is the entry received on the j-th received antenna andjε{1, . . . , N_(R)};

[0041] x is the transmitted vector, i.e., x[x₁ x₂ . . . x_(N) _(T)]^(T), where {x_(i)} is the entry transmitted from the i-th transmitantenna and iε{1, . . . , N_(T)};

[0042] H is the channel response matrix for the MIMO channel;

[0043] A is a diagonal matrix of the amplitudes of the data streams,{A_(i)};

[0044] n is the additive white Gaussian noise (AWGN) with a mean vectorof 0 and a covariance matrix of Λ_(n)=σ²I, where 0 is a vector of zeros,I is the identity matrix with ones along the diagonal and zeroseverywhere else, and σ² is the variance of the noise; and

[0045] [.]^(T) denotes the transpose of [.].

[0046] The diagonal matrix, A, may be expressed as: $\begin{matrix}{{\underset{\_}{A} = \begin{bmatrix}A_{1} & 0 & \ldots & 0 \\0 & A_{2} & \ldots & 0 \\\vdots & \vdots & ⋰ & \vdots \\0 & 0 & \ldots & A_{N_{T}}\end{bmatrix}},} & {{Eq}\quad (2)}\end{matrix}$

[0047] where A_(i) represents the amplitude of the data stream x_(i)transmitted from the i-th transmit antenna. The amplitude A_(i) and thetransmit power P_(i) of data stream x_(i) are related by P_(i)∝A_(i) ².

[0048] The model for the MIMO system may be expressed in a more compactform, as follows:

y=Cx+n,  Eq (3)

[0049] where the composite channel matrix, C, is defined as C=HA.

[0050] For simplicity, the MIMO channel is assumed to be a flat-fading,narrowband channel. In this case, the elements of the channel responsematrix, H, are scalars, and the coupling, h_(j,i), between eachtransmit-receive antenna pair can be represented by a single scalarvalue. However, the power control techniques described herein may alsobe used for a frequency selective channel having different channel gainsat different frequencies. In such a frequency selective channel, theoperating bandwidth may be divided into a number of (equal or unequalwidth) frequency bands such that each band may be considered as aflat-fading channel. The response of the individual bands may then beconsidered in performing power control.

[0051] Due to scattering in the propagation environment, the N_(S) datastreams transmitted from the N_(T) transmit antennas interfere with eachother at the receiver. In particular, a given data stream transmittedfrom one transmit antenna may be received by all N_(R) receive antennasat different amplitudes and phases. Each received signal may theninclude a component from each of the N_(T) transmitted data streams. TheN_(R) received signals would collectively include all N_(T) transmitteddata streams; however, these data streams are dispersed among thereceived signals.

[0052] Various processing techniques may be used at the transmitter andreceiver to ameliorate the effects of interference. These processingtechniques depend on the available CSI and the characteristics of theMIMO channel

[0053] The processing at the transmitter and receiver is dependent onthe available CSI, which may be categorized as either “full CSI” or“partial CSI”. Full CSI includes sufficient characterization (e.g.,amplitude and phase) across the entire system bandwidth for thepropagation path between each transmit-receive antenna pair in a(N_(R)×N_(T)) MIMO matrix. Full CSI may not be available or practicalfor many systems. Partial CSI may comprise, for example, the SNRs of thetransmission channels.

[0054] For a MIMO system utilizing partial CSI, at the transmitter eachdata stream may be coded and modulated in accordance with a particularcoding and modulation scheme selected based on the achievable SNR. Inthe partial-CSI system, one data stream may be transmitted on eachantenna and the transmit power for each data stream may also be adjustedbased on the SNR and the selected coding and modulation scheme.

[0055] At the receiver, various receiver processing techniques may beused to process the received signals to recover the transmitted datastreams. These receiver processing techniques may be grouped into twoprimary categories:

[0056] spatial and space-time receiver processing techniques (which arealso referred to as equalization techniques), and

[0057] “successive nulling/equalization and interference cancellation”receiver processing technique (which is also referred to as “successiveinterference cancellation” or “successive cancellation” receiverprocessing technique).

[0058] In general, the spatial and space-time receiver processingtechniques attempt to separate out the transmitted data streams at thereceiver. Each transmitted data stream may be “detected” by combiningthe various components of the transmitted data streams included in theN_(R) received signals based on an estimate of the channel response andremoving (or canceling) the interference due to the components of theother data streams. These receiver processing techniques attempt toeither (1) decorrelate the received data streams such that there is nointerference from the other data streams or (2) maximize the SNR of eachdata stream in the presence of noise and interference from the otherdata streams. Each detected data stream is then further processed (e.g.,demodulated, deinterleaved, and decoded) to recover the traffic data forthe data stream.

[0059] The successive cancellation receiver processing techniqueattempts to recover the transmitted data streams, one at a time using aspatial or space-time receiver processing technique, and to cancel theinterference due to each recovered data stream such that later recovereddata streams experience less interference and may be able to achievehigher SNR. The successive cancellation receiver processing techniquemay be used if the interference due to each recovered data stream can beaccurately estimated and canceled, which requires error free recovery ofthe data stream. The successive cancellation receiver processingtechnique generally outperforms the spatial/space-time receiverprocessing techniques.

[0060] The specific receiver processing technique to be used istypically dependent on the characteristics of the MIMO channel, whichmay be characterized as either non-dispersive or dispersive. Anon-dispersive MIMO channel experiences flat fading (i.e., approximatelyequal amount of attenuation across the system bandwidth), and adispersive MIMO channel experiences frequency-selective fading (e.g.,different amounts of attenuation across the system bandwidth).

[0061] For a non-dispersive MIMO channel, spatial receiver processingtechniques may be used to process the received signals to provide thedetected data streams. These spatial receiver processing techniquesinclude a channel correlation matrix inversion (CCMI) technique and aminimum mean square error (MMSE) technique. Other spatial receiverprocessing techniques may also be used and are within the scope of theinvention.

[0062] For a dispersive MIMO channel, time dispersion in the channelintroduces inter-symbol interference (ISI). To improve performance, areceiver attempting to recover a particular transmitted data streamwould need to ameliorate both the interference (or “crosstalk”) from theother transmitted data streams as well as the ISI from all data streams.To combat both crosstalk and ISI, space-time receiver processingtechniques may be used to process the received signals to provide thedetected data streams. These space-time receiver processing techniquesinclude a MMSE linear equalizer (MMSE-LE), a decision feedback equalizer(DFE), a maximum-likelihood sequence estimator (MLSE), and so on.

[0063] For clarity, the power control techniques are describedspecifically for the CCMI and MMSE techniques, each with and withoutsuccessive cancellation. The power control techniques may similarly beapplied to other receiver processing techniques, and this is within thescope of the invention.

Power Control

[0064] In a MIMO system with N_(T) transmit and N_(R) receive antennas,the number of resolvable data streams is N_(S)≦min {N_(T), N_(R)} when His a full-rank matrix. The set of data streams may be represented as{x₁, x₂, . . . , x_(N) _(S) }, or {x_(i)} for iεD where D={1, . . . ,N_(S)}. Each data stream is associated with a particular“post-detection” SNR, γ_(post), after the spatial or space-time receiverprocessing at the receiver. The post-detection SNR of data stream x_(i)may be expressed as: $\begin{matrix}{{{\gamma_{post}(i)} = \frac{P_{i}}{I_{i}}},{{for}\quad {\forall{i \in D}}},} & {{Eq}\quad (4)}\end{matrix}$

[0065] where P_(i) represents the transmit power of data stream x_(i)(i.e., P_(i)=|x_(i)|²), and I_(i) represents the noise and interferenceexperienced by data stream x_(i) (e.g., from the other data streams).The post-detection SNRs are dependent on the characteristics of the MIMOchannel and may be different for different data streams. If successivecancellation receiver processing technique is used, then thepost-detection SNRs may also differ depending on the particular order inwhich the data streams are detected at the receiver, as described below.

[0066] The post-detection SNR of each data stream contributes to theoverall spectral efficiency of the MIMO system. The spectral efficiencyof a given data stream may be defined based on a particularmonotonically increasing function in post-detection SNR. One functionthat may be used for spectral efficiency is the capacity function. Inthis case, the spectral efficiency, ρ_(i), of data stream x_(i), foriεD, may be expressed as:

ρ_(i)=log₂(1+γ_(post)(i)),  Eq (5)

[0067] and is typically given in units of bits per second per Hertz(bps/Hz).

[0068] The total spectral efficiency, ρ_(tot), of the MIMO system isequivalent to that of a system with N_(S) parallel single-input,single-output (SISO), non-interfering channels, and may be expressed as:$\begin{matrix}{\rho_{tot} = {\sum\limits_{i = 1}^{N_{s}}{\rho_{i}.}}} & {{Eq}\quad (6)}\end{matrix}$

[0069]FIG. 2 shows two plots for spectral efficiency versuspost-detection SNR. Plot 212 shows spectral efficiency increasinglogarithmically with SNR as computed based on equation (5), whichassumes that an increase in SNR results in a corresponding increase inspectral efficiency. However, in a practical communication system, theremay be an upper limit on the spectral efficiency, which may be dictated,for example, by the maximum data rate supported by the system for anygiven data stream. Plot 214 shows spectral efficiency increasinglogarithmically at lower SNRs and saturating at ρ_(set), which is theupper limit on spectral efficiency. Saturation occurs when an increasein SNR no longer produces an increase in spectral efficiency. The SNR atwhich spectral efficiency saturates may be denoted as γ_(set) (i.e.,γ_(set)⇄ρ_(set))

[0070] In typical systems, there is a power limit on each transmitantenna. In some systems, the total transmit power, P_(tot), availablefor use for all N_(T) transmit antennas may be initially allocated tothe data streams in some manner, as long as the power limit per antennais not exceeded. For example, if the power limit on each of the N_(T)transmit antennas is P_(tot)/N_(T) and one data stream is transmittedfrom each antenna, then the total transmit power may be uniformlydistributed such that each of the N_(T) transmit antennas is initiallyallocated P_(tot)/N_(T), and therefore, each data stream is alsoallocated P_(tot)/N_(T). This is true even if only some of theseantennas are used for data transmission. In this case, if N_(S)<N_(T),each transmit antenna may be allocated at most P_(tot)/N_(T), and eachdata stream is also transmitted at P_(tot)/N_(T) power. In thissituation when the number of data streams is less than the number oftransmit antennas, the total power used at the transmitter is less thanP_(tot) and equal to N_(S)·P_(tot)/N_(T).

[0071] Depending on the transmit powers, P_(i), for iεD, used for thedata streams and the noise variance, σ², the post-detection SNRs of somedata streams may be higher than γ_(set). Although post-detection SNRsabove γ_(set) may lower the frame error rate (FER), this type ofimprovement in performance is typically not substantial since the systemmay already be operating at the target FER or at a low FER. In thiscase, the excess transmit power that results in the SNR being higherthan γ_(set) is not effectively utilized and also causes additionalinterference to other data streams. The transmit power used for eachdata stream with a post-detection SNR greater than γ_(set) may thus bereduced so that the new post-detection SNR is at or near γ_(set).

[0072] Similarly, in some systems, there may be a particular target SNRat the receiver for each data stream, which is also commonly referred toas the setpoint. The target SNR is the post-detection SNR needed toachieve the target FER for a particular data rate and may also berepresented as γ_(set). For a power-controlled MIMO system, if thetransmit power currently used for a given data stream results in apost-detection SNR different than the setpoint, then the transmit powerfor this data stream may be adjusted either up or down such that the newpost-detection SNR approaches the setpoint. The setpoint may also beadjusted (e.g., based on the detected frame errors or erasures) toachieve the target FER.

[0073] Techniques are provided herein to control the transmit powers forthe data streams in a MIMO system such that various benefits may beachieved. The post-detection SNRs of the data streams may be initiallyestimated. The transmit power for each data stream is then determined bytaking into account the specific receiver processing technique used todetect the data streams at the receiver. The new transmit powers attemptto maintain the post-detection SNRs of the detected data streams at orbelow the saturation post-detection SNR (for a system with an upperlimit on spectral efficiency) or at or near the setpoint (for a systemwith a specified spectral efficiency).

[0074] As noted above, the post-detection SNRs of the data streams aredependent on the particular receiver processing technique used at thereceiver to detect the data streams. Moreover, the relationships betweentransmit powers and post-detection SNRs for the detected data streamsmay be decorrelated or not decorrelated for different receiverprocessing techniques. Different power control schemes are providedherein for different classes of receiver processing techniques withdifferent characteristics. In the first class, the detected data streamsare decoupled by the receiver processing, and changing the transmitpower of one data stream does not affect the post-detection SNRs of theother data streams. This first class includes the CCMI and CCMI withsuccessive cancellation (i.e., CCMI-SC) receiver processing techniques.In the second class, the post-detection SNR of a given data stream maybe coupled to one or more of the other data streams' transmit powers,and a change in transmit power for one data stream may affect thepost-detection SNRs of the other data streams. This second classincludes the MMSE and MMSE with successive cancellation (i.e., MMSE-SC)receiver processing techniques. Power control for the CCMI, CCMI-SC,MMSE, and MMSE-SC receiver processing techniques are described infurther detail below.

Power Control for CCMI Receiver

[0075] The CCMI receiver processing technique (which is also known as adecorrelation or a zero-forcing technique) is an interferencecancellation technique that does not require full CSI at thetransmitter. With the CCMI technique, the transmitter can transmit anindependent data stream from each transmit antenna. The receiver firstperforms a channel matched-filter operation on the received vector, y,which is representative of the received symbol streams. The resultingvector, {tilde over (x)}, may be expressed as: $\begin{matrix}\begin{matrix}{\underset{\_}{\overset{\sim}{x}} = {{\underset{\_}{C}}^{H}\underset{\_}{y}}} \\{{= {{{\underset{\_}{C}}^{H}\underset{\_}{Cx}} + {{\underset{\_}{C}}^{H}\underset{\_}{n}}}},}\end{matrix} & {{Eq}\quad (7)}\end{matrix}$

[0076] where [.]^(H) denotes the conjugate transpose of [.].

[0077] A composite channel correlation matrix, R, may be defined as:

R=C ^(H) C.  Eq (8)

[0078] Equation (7) can then be rewritten as:

{tilde over (x)}=Rx+C _(H) n.  Eq (9)

[0079] Since R is a square matrix of dimension N_(T), the interferenceit causes to the transmitted data streams, x, can be cancelled bymultiplying {tilde over (x)} by the inverse of R, R⁻¹, to obtain thefollowing: $\begin{matrix}\begin{matrix}{\underset{\_}{\hat{x}} = {{\underset{\_}{R}}^{- 1}\underset{\_}{\overset{\sim}{x}}}} \\{= {{{\underset{\_}{R}}^{- 1}\underset{\_}{Rx}} + {{\underset{\_}{R}}^{- 1}{\underset{\_}{C}}^{H}\underset{\_}{n}}}} \\{= {\underset{\_}{x} + {\underset{\_}{\overset{\sim}{n}}.}}}\end{matrix} & {{Eq}\quad (10)}\end{matrix}$

[0080] The vector {circumflex over (x)} is representative of thedetected data streams, which are estimates of the transmitted datastreams. The covariance matrix of ñ may be expressed as:

{tilde over (Λ)}_(n)=(R ⁻¹ C ^(H))Λ_(n)(R ⁻¹ C ^(H))^(H) =R ⁻¹σ².  Eq(11)

[0081] Due to the structure of R⁻¹, the CCMI technique may amplify thenoise.

[0082] For the CCMI technique, the post-detection SNR of data streamx_(i) may be expressed as: $\begin{matrix}{{{\gamma_{ccmt}(i)} = \frac{P_{i}}{{\overset{\Cup}{r}}_{ii}\sigma^{2}}},{{for}\quad {\forall{i \in D}}},} & {{Eq}\quad (12)}\end{matrix}$

[0083] where P_(i) is the transmit power for data stream x_(i), σ² isthe noise power at the receiver, and {haeck over (r)}_(u) is the i-thdiagonal element of R⁻¹. It can be noted that there is no interferenceterm in the denominator in equation (12). This results from the factthat the data streams are decorrelated by the CCMI processing and thusdo not interfere with each other.

[0084] The CCMI receiver processing technique is described in furtherdetail in U.S. patent application Ser. No. 09/993,087, entitled“Multiple-Access Multiple-Input Multiple-Output (MIMO) CommunicationSystem,” filed Nov. 6, 2001; U.S. patent application Ser. No.09/854,235, entitled “Method and Apparatus for Processing Data in aMultiple-Input Multiple-Output (MIMO) Communication System UtilizingChannel State Information,” filed May 11, 2001; and U.S. patentapplication Ser. Nos. 09/826,481 and 09/956,449, both entitled “Methodand Apparatus for Utilizing Channel State Information in a WirelessCommunication System,” respectively filed Mar. 23, 2001 and Sep. 18,2001. These applications are all assigned to the assignee of the presentapplication and incorporated herein by reference.

[0085] A key goal of power control is to use the least amount oftransmit power to obtain the highest possible spectral efficiency. TheCCMI receiver processing provides a set of post-detection SNRs for thedetected data streams. As noted above, there may be an upper limit onthe spectral efficiency of a given data stream. This spectralefficiency, ρ_(set), corresponds to the SNR γ_(set). If thepost-detection SNR of any given data stream is greater than γ_(set),then the transmit power for that data stream may be adjusted to reducetransmit power without impacting spectral efficiency.

[0086]FIG. 3 is a flow diagram of a process 300 for adjusting thetransmit power to achieve a set of post-detection SNRs for a CCMIreceiver. Process 300 determines the minimum total transmit power neededto achieve a set of post-detection SNRs that maximize spectralefficiency. Initially, the variable i used to denote the data streamnumber is initialized to one (i.e., i=1) (step 312). Each post-detectionSNR in the set is then examined and the new transmit power, {circumflexover (P)}_(i), to use for the corresponding data stream is determinedstarting at step 314.

[0087] For each data stream, a determination is first made whether ornot the post-detection SNR, γ_(post)(i), is greater than γ_(set) (step314). (In the figures, γ_(post)(i) is denoted as SNR(i) and γ_(set) isdenoted as SNR_(set).) If the answer is no, then the transmit power forthis data stream is not adjusted (i.e., {circumflex over (P)}_(i)=P_(i))and the process proceeds to step 320. Otherwise, if γ_(post)(i)>γ_(set),then the new transmit power, {circumflex over (P)}_(i), for data streamx_(i) that achieves γ_(post)(i)=γ_(set) is determined (step 316). Therelationship between {circumflex over (P)}_(i) and γ_(set) may beexpressed as: $\begin{matrix}{\gamma_{set} = {\frac{{\hat{P}}_{i}}{{\overset{\Cup}{r}}_{ii}\sigma^{2}}.}} & {{Eq}\quad (13)}\end{matrix}$

[0088] Using equation (13) together with equation (12) for the CCMItechnique, the new transmit power to use for data stream x_(i) may beexpressed as: $\begin{matrix}{{{\hat{P}}_{i} = {\frac{\gamma_{set}}{\gamma_{post}(i)}P_{i}}},} & {{Eq}\quad (14)}\end{matrix}$

[0089] where γ_(post)(i)=γ_(ccmi)(i) for the CCMI technique. The simplerelationship seen in equation (14) is a result of the linearrelationship between the post-detection SNR and the transmit power, asshown in equation (12).

[0090] A determination is then made whether or not all post-detectionSNRs in the set have been considered (step 320). If the answer is no,then the variable i is incremented (step 322), and the process returnsto step 314 to evaluate another post-detection SNR in the set.Otherwise, the process terminates.

[0091] The process shown in FIG. 3 results in a set of transmit powers,{{circumflex over (P)}_(i)}, for iεD, to be used for the data streams.This set includes transmit powers that have been adjusted to achieveγ_(set).

[0092] If any initial post-detection SNRs are greater than γ_(set), thenthe new transmit powers, {circumflex over (P)}_(i), to bring thesepost-detection SNRs to γ_(set) will be lower than the initial transmitpowers, P_(i). The total power saved may be determined as:$\begin{matrix}{{{\Delta \quad P_{total}} = {{10\quad {\log_{10}\left( {\sum\limits_{i = 1}^{N_{s}}P_{i}} \right)}} - {10\quad {\log_{10}\left( {\sum\limits_{i = 1}^{N_{s}}{\hat{P}}_{i}} \right)}}}},} & {{Eq}\quad (15)}\end{matrix}$

[0093] where the new transmit power, {circumflex over (P)}_(i), may ormay not be equal to the initial transmit power, P_(i), depending onwhether or not the initial post-detection SNR is greater than γ_(set).

Power Control for CCMI-SC Receiver

[0094] The CCMI technique may be used in conjunction with successiveinterference cancellation. For the CCMI-SC technique, the receivedsymbol streams are processed using CCMI spatial receiver processing torecover one data stream at a time based on a particular detection order.As each data stream is recovered, the interference it causes to theother, not yet recovered data streams is estimated using the compositechannel matrix, C. The estimated interference is then subtracted orcanceled from the received symbol streams, and the modified symbolstreams are then processed to recover the next data stream. For thisrecursive technique, the composite channel matrix is successivelyshortened at each stage to exclude the data stream that has just beenrecovered, and the process is repeated until all data streams have beenrecovered.

[0095]FIG. 4 is a flow diagram illustrating a process 400 for theCCMI-SC receiver processing technique. Initially, the N_(R) receivedsignals are processed to obtain N_(R) corresponding received symbolstreams (which are denoted as the received vector, y) (step 412). Thecomposite channel matrix, C, is also estimated, for example, based onthe pilot included in the data transmission (also step 412). A specificorder for detecting the data streams is received (step 414). Thisdetection order may be represented as D={d₁, d₂, . . . d_(N) _(T) },where d_(k) is the identity of the data stream to be recovered in thek-th stage. The variable k used to denote the iteration (or stage)number is initialized to one (i.e., k=1) for the first iteration, andthe variable i is set as i=d_(k) (step 416).

[0096] For the first iteration to detect the first data stream in thedetection order D, the CCMI spatial receiver processing is initiallyperformed on the received symbol streams (step 422). This is achieved byperforming the channel matched-filter operation on the received vector,y, as shown in equation (7), and then pre-multiplying the resultantvector, {tilde over (x)}, with the inverse composite channel correlationmatrix, R⁻¹, as shown in equation (10), to provide N_(S) detected datastreams. One particular detected data stream, {circumflex over (x)}_(i),is then selected, as determined by the received detection order, and thepost-detection SNR, γ_(post)(i), for this data stream is estimated,(step 424). The detected data stream, {circumflex over (x)}_(i), mayfurther be processed (e.g., demodulated, deinterleaved, and decoded) torecover the transmitted traffic data for the data stream (step 426).

[0097] A determination is then made whether or not all data streams havebeen detected (step 428). If the answer is yes, then the receiverprocessing terminates. Otherwise, the interference due to the detecteddata stream x_(i) on the remaining, not yet detected data streams isestimated (step 430). The interference may be estimated by firstre-encoding the decoded data for the detected data stream, interleavingthe re-encoded data, and symbol-mapping the interleaved data (using thesame coding, interleaving, and modulation schemes used at thetransmitter for this data stream) to obtain a “remodulated” symbolstream. The remodulated symbol stream is an estimate of the i-th symbolstream previously transmitted from one of the N_(T) transmit antennas.The remodulated symbol stream is then convolved by the elements of acomposite channel vector, c_(i) (which is the i-th column of the matrixC and corresponds to the detected data stream {circumflex over (x)}_(i))to derive a vector i^(k) of N_(R) interference components due to thisdata stream at the k-th stage.

[0098] The estimated interference due to the detected data stream,{circumflex over (x)}_(i), is then subtracted from the received symbolstreams to derive the modified symbol streams for the next iteration(i.e., y^(k+1)=y^(k)−i^(k), where y¹=y) (step 432). These modifiedsymbol streams represent the received symbol streams that would havebeen obtained at the receiver if the detected data stream x_(i) had notbeen transmitted (i.e., assuming that the interference cancellation waseffectively performed).

[0099] A modified composite channel matrix, C_(k+1), is then obtained byremoving the column c_(i) corresponding to the detected data streamx_(i) (step 434). The matrix C_(k+1) is thus reduced to N_(R)×(N_(T)−1)after the first iteration. The variable k is then incremented for thenext iteration (i.e., k=k+1) and the variable i is again set as i=d_(k)(step 436). The process then returns to step 422 to recover the nextdata stream.

[0100] The processing shown in FIG. 4 is thus repeated on the modifiedsymbol streams to recover the remaining data streams. In particular,steps 422 through 426 are performed for each data stream to berecovered, and steps 430 through 436 are performed if there is anotherdata stream to be recovered.

[0101] For the first iteration, the received symbol streams areprocessed using the CCMI technique. And for each subsequent iteration,the modified symbol streams (i.e., after the interference cancellation)are processed using the CCMI technique. The processing for eachiteration proceeds in similar manner with the proper substitution forthe input symbol streams. At each iteration subsequent to the firstiteration, the interference due to the data streams recovered in theprevious iterations is assumed to be cancelled, and the dimensionalityof the composite channel matrix is reduced.

[0102] The CCMI-SC receiver processing technique is described in furtherdetail in the aforementioned U.S. patent application Ser. Nos.09/993,087, 09/854,235, 09/826,481, and 09/956,449.

[0103] For the CCMI-SC technique, the post-detection SNR of data streamx_(i) may be expressed as: $\begin{matrix}{{{\gamma_{{ccmi} - {sc}}(i)} = \frac{P_{i}}{{\overset{\Cup}{r}}_{ii}\sigma^{2}}},{{for}\quad {\forall{i \in D}}}} & {{Eq}\quad (16)}\end{matrix}$

[0104] where {haeck over (r)}_(u) is the i-th diagonal element of R_(k)⁻¹, and the matrices applied at the receiver, C_(k) and R_(k) ⁻¹, arere-determined at each stage of the detection process since thesematrices change as the data streams are detected and the interferencethey cause to the other data streams is removed.

[0105] When throughput is a monotonically increasing function of thepost-detection SNRs, as shown in equation (5), the order in which thedata streams are recovered at the receiver may or may not have an impacton the overall spectral efficiency, depending on the type of receiveremployed. For the CCMI-SC receiver, changing the detection order affectsthe overall spectral efficiency.

[0106] Since different detection orders may be associated with differentspectral efficiencies for the CCMI-SC receiver, a number of detectionorders may be evaluated to determine the specific detection order thatprovides the best spectral efficiency among the ones evaluated. Anexhaustive search may also be performed over all possible detectionorders to obtain the specific detection order that achieves the highestpossible spectral efficiency. In any case, the transmit power may beadjusted to achieve the required post-detection SNRs for the detectionorder with the best spectral efficiency.

[0107]FIG. 5 is a flow diagram of a process 500 for maximizing spectralefficiency while minimizing the total required transmit power for theCCMI-SC receiver. Initially, a list of detection orders to be evaluatedis determined (step 512). In one embodiment, all possible detectionorders are evaluated. In this case, for a system with N_(S) datastreams, there are N_(S) factorial (N_(S)!) possible detection orders.The variable used to denote the maximum spectral efficiency achieved byall evaluated detection orders is initialized to zero (i.e., ρ_(max)=0)(step 514), and the variable n used to denote the iteration number isinitialized to one (i.e., n=1) for the first iteration (step 516). Thefirst detection order is then evaluated starting at step 520.

[0108] For the current detection order, D_(n), to be evaluated, thereceived symbol streams are initially processed using the CCMI-SCtechnique and based on that detection order to obtain a set ofpost-detection SNRs for the detected data streams (step 520). Step 520may be performed using the process shown in FIG. 4. For eachpost-detection SNR in the set that is greater than γ_(set), thepost-detection SNR is adjusted by setting it to γ_(set) (i.e.,γ_(post)(i)=γ_(set)) (step 522). The total spectral efficiency, ρ_(n),for all detected data streams for the current detection order is thendetermined based on the adjusted post-detection SNRs, as shown inequations (5) and (6) (step 524).

[0109] A determination is then made whether or not the spectralefficiency, ρ_(n), for the current detection order is higher than thebest spectral efficiency obtained thus far (step 526). If the answer isno, then the process proceeds to step 530. Otherwise, the spectralefficiency for the current detection order is saved as the new bestspectral efficiency (i.e., ρ_(max)=ρ_(n)), and the set of post-detectionSNRs for this detection order is also saved (step 528).

[0110] A determination is then made whether or not all detection ordersin the list have been evaluated (step 530). If the answer is no, thenthe variable n is incremented for the next iteration (i.e., n=n+1) (step532), and the process returns to step 520 to evaluate the next detectionorder. Otherwise, if all detection orders have been evaluated, then thetransmit power needed to achieve the post-detection SNRs correspondingto the best spectral efficiency is determined (step 534). Step 534 maybe performed as shown in FIG. 3. The process then terminates.

[0111] For the CCMI-SC technique, when N_(S)=2, the highest spectralefficiency results when the data stream with the smaller post-detectionSNR is recovered first and the one with the higher post-detection SNR isrecovered last. For N_(S)>2, the optimality of the min-to-max γ_(post)detection order decreases as the number of data streams, N_(S),increases.

[0112] The maximum spectral efficiency, ρ_(max), obtained for allevaluated detection orders, as determined by the process shown in FIG.5, uses the adjusted post-detection SNR of γ_(post)=γ_(set) for thedetected data streams whose initial post-detection SNRs exceededγ_(set). The transmit power that achieves the set of adjustedpost-detection SNRs corresponding to ρ_(max) is then determined. Becausethe detected data streams are decoupled at the output of the CCMI-SCreceiver, changing the transmit power of one data stream does not affectthe post-detection SNR of any other data stream. Thus, the determinationof the transmit power that achieves an adjusted post-detection SNR ofγ_(set) can be made independently for each data stream whose initialpost-detection SNR exceeds γ_(set).

[0113] The process shown in FIG. 3 may be used to determine the transmitpowers needed to achieve the set of adjusted post-detection SNRscorresponding to the maximum spectral efficiency, ρ_(max). For eachinitial post-detection SNR in the set that is greater than γ_(set), thenew transmit power, {circumflex over (P)}_(i), to be used for the datastream to achieve γ_(post)(i)=γ_(set) may be expressed as:$\begin{matrix}{{{\hat{P}}_{i} = {\frac{\gamma_{set}}{\gamma_{post}(i)}P_{i}}},} & {{Eq}\quad (17)}\end{matrix}$

[0114] where γ_(post)(i)=γ_(ccmi-sc)(i) for the CCMI-SC technique.

[0115] The result of the power adjustment in FIG. 3 is a set of transmitpowers, {{circumflex over (P)}_(i)}, for iεD, to be used for the datastreams. This set includes transmit powers that have been adjusted toachieve γ_(set). The total power saved for the new transmit powers maybe determined based on equation (15).

Power Control for MMSE Receiver

[0116] For the MMSE spatial receiver processing technique, thetransmitter can also transmit an independent data stream from eachtransmit antenna. The receiver performs a multiplication of the receivedvector, y, with two matrices, M and D_(v) ⁻¹, to derive an unbiased MMSEestimate, {circumflex over (x)}, of the transmit vector, x. The unbiasedMMSE estimate may be expressed as:

{circumflex over (x)}=D _(v) ⁻¹ My,   Eq (18)

[0117] where

[0118] y=x+n;

[0119] M=C^(T)(CC^(T)+Λ_(n))⁻¹; and

[0120] D_(v) ⁻¹=diag(1/v₁₁, 1/v₂₂, . . . 1/v_(N) _(T) _(N) _(T) ),

[0121] where v_(u) are the diagonal elements of the matrix V, which isdefined as:

V=MC.  Eq (19)

[0122] The matrix M is selected such that the mean square error betweenthe MMSE estimate, {circumflex over (x)}, and the transmitted vector, x,is minimized. The matrix D_(v) ⁻¹ is used to ensure that {circumflexover (x)} is an unbiased estimate of x.

[0123] For the MMSE technique, the post-detection SNR of data streamx_(i) may be expressed as: $\begin{matrix}{{{\gamma_{mmse}(i)} = {\frac{v_{u}}{1 - v_{\overset{.}{u}}}P_{i}}},{{for}\quad {\forall{i \in D}}},} & {{Eq}\quad (20)}\end{matrix}$

[0124] where P_(i) is the transmit power for data stream x_(i) and v_(n)is the i-th diagonal element of the matrix V. Equation (20) may berewritten as: $\begin{matrix}{{{\gamma_{mmse}(i)} = \frac{P_{i}}{\alpha_{i}}},} & {{Eq}\quad (21)}\end{matrix}$

[0125] where$\alpha_{i} = {\frac{1 - v_{\overset{.}{u}}}{v_{\overset{¨}{u}}}.}$

[0126] It can be observed in equations (20) and (21) that thepost-detection SNR of data stream x_(i) is a linear function of thetransmit power P_(i) for data stream x_(i).

[0127] The MMSE receiver processing technique is described in furtherdetail in the aforementioned U.S. patent application Ser. Nos.09/993,087, 09/854,235, 09/826,481, and 09/956,449.

[0128] Power control may also be used for the MMSE receiver to maximizespectral efficiency while minimizing transmit power. The MMSE processingprovides a set of post-detection SNRs for the detected data streams. Ifthe post-detection SNR of any given data stream is greater than γ_(set),then the transmit power for the data stream may be adjusted to reducetransmit power without impacting spectral efficiency.

[0129] One property of the MMSE technique is that it does notdecorrelate the transmitted data streams. Thus, the post-detection SNRof one data stream may be a function of the transmit powers of any ofthe other data streams. Because the MMSE technique does not decorrelatethe data streams, a change in the transmit power of one data stream hasthe potential to affect the post-detection SNRs of all the other datastreams. The power control for the MMSE receiver may then be performediteratively to achieve the desired results.

[0130]FIG. 6 is a flow diagram of a process 600 for adjusting thetransmit power to achieve a set of post-detection SNRs for the MMSEreceiver. Process 600 determines the minimum total transmit power neededto achieve a set of post-detection SNRs that maximize spectralefficiency for the MMSE receiver. Initially, the MMSE spatial receiverprocessing is performed on the received symbol streams to obtain a setof post-detection SNRs for the detected data streams (step 608). Avariable Repeat used to indicate whether or not to repeat the poweradjustment is set to “No” (step 610), and the variable i used to denotethe data stream number is initialized to one (i.e., i=1) (step 612).Each post-detection SNR in the set is then examined and the new transmitpower, {circumflex over (P)}_(i), to use for the corresponding datastream is determined starting at step 614.

[0131] For each data stream, a determination is first made whether ornot the post-detection SNR, γ_(post)(i), is greater than γ_(set) (step614). Alternatively, the power adjustment may only be made ifγ_(post)(i) is greater than γ_(set) plus some delta (i.e.,γ_(post)(i)>(γ_(set)+γΔ)) If the answer is no, then the transmit powerfor this data stream is not adjusted (i.e., {circumflex over(P)}_(i)=P_(i)) and the process proceeds to step 620. Otherwise, the newtransmit power, {circumflex over (P)}_(i), for data stream x_(i) thatachieves γ_(post)(i)=γ_(set) is determined (step 616). The relationshipbetween {circumflex over (P)}_(i) and γ_(set) may be expressed as:$\begin{matrix}{\gamma_{set} = {\frac{{\hat{P}}_{i}}{\alpha_{i}}.}} & {{Eq}\quad (22)}\end{matrix}$

[0132] Using equation (22) together with equation (21) for the MMSEtechnique, the transmit power to use for data stream x_(i) may beexpressed as: $\begin{matrix}{{{\hat{P}}_{i} = {\frac{\gamma_{set}}{\gamma_{post}(i)}P_{i}}},} & {{Eq}\quad (23)}\end{matrix}$

[0133] where γ_(post)(i)=γ_(mmse)(i) for the MMSE receiver.

[0134] Since decreasing the transmit power for data stream x_(i) mayincrease the post-detection SNR of some other data stream to be higherthan γ_(set), the variable Repeat is set to “Yes” (step 618). This wouldthen result in the re-evaluation of the set of adjusted post-detectionSNRs via one more subsequent iteration through the set if the transmitpower for any data stream is reduced in the current iteration.

[0135] A determination is then made whether or not all post-detectionSNRs in the set have been considered (step 620). If the answer is no,then the variable i is incremented (step 622), and the process returnsto step 614 to evaluate another post-detection SNR in the set.

[0136] Otherwise, if all SNRs in the set have been considered, then adetermination is made whether or not Repeat is set to “Yes” (step 624).If the answer is no, indicating that the transmit power was not adjustedfor any data stream in the last iteration, then the process terminates.Otherwise, the process returns to step 608 to perform another iterationthrough the set of post-detection SNRs.

[0137] For each subsequent iteration to possibly readjust the transmitpowers for the data streams, the transmit powers, {P̂_(i)},

[0138] for iεD, determined in the prior iteration are used for the MMSEprocessing. In particular, the new amplitudes, {A_(i)}, for iεD, of thedata streams are initially determined based on the new transmit powers,{P̂_(i)},

[0139] for iεD, to derive a new composite channel matrix, C. Thematrices M and ${\underset{\_}{D}}_{v}^{- 1}$

[0140] are then updated based on the new composite channel matrix, asshown in equation (18). The updated matrices M and${\underset{\_}{D}}_{v}^{- 1}$

[0141] are then used for the MMSE processing of the received symbolstreams in step 608.

[0142] The power control process shown in FIG. 6 results in a set oftransmit powers, {P̂_(i)},

[0143] for iεD, to be used for the data streams. This set includes thetransmit powers that have been adjusted to achieve γ_(set). The totalpower saved may be determined using equation (15).

Power Control for MMSE-SC Receiver

[0144] The MMSE technique may also be used in conjunction withsuccessive interference cancellation. For the MMSE-SC technique, thereceived vector, y, is processed in a recursive manner using MMSEspatial receiver processing to recover one data stream at a time basedon a particular detection order. The MMSE-SC technique may beimplemented using the process shown in FIG. 4, except that MMSE spatialreceiver processing is performed in step 422 instead of CCMI spatialreceiver processing. The result of the processing shown in FIG. 4 is aset of post-detection SNRs for the detected data streams.

[0145] For the MMSE-SC technique, the post-detection SNR of data streamx_(i) may be expressed as shown in equation (20), which is:${{\gamma_{{mmse}\text{-}{sc}}(i)} = {\frac{v_{ii}}{1 - v_{ii}}P_{i}}},{{for}\quad {\forall{i \in {D.}}}}$

[0146] However, the matrix V is different for different stages of theMMSE-SC receiver. The post-detection SNR of data stream x_(i) may thusbe different depending on the particular stage in which it is recovered.

[0147] One property of the MMSE-SC receiver is that it does notdecorrelate the data streams. This is because the underlying MMSEtechnique used for the spatial receiver processing at each stage doesnot decorrelate the data streams. For each stage of the MMSE-SCreceiver, one data stream is recovered and the post-detection SNR ofthis data stream may be a function of the transmit powers of all thedata streams not yet recovered. Once this data stream has beenrecovered, its interference effect on the remaining, not yet recovereddata streams is estimated and removed. If the interference cancellationis effective, then this data stream has no (or minimal) effect onsubsequently recovered data streams, and the transmit power of this datastream does not effect the post-detection SNRs of subsequently recovereddata streams. Thus, adjusting the transmit power of a given data streamx_(i) may affect the post-detection SNRs of the data streams recoveredprior to x_(i) but not those recovered after x_(i) (again, if theinterference cancellation is effectively performed). To reducecomputational complexity, the transmit powers for the data streams maybe adjusted using reverse detection order.

[0148]FIG. 7 is a flow diagram of a process 700 for adjusting thetransmit power to achieve a set of post-detection SNRs for the MMSE-SCreceiver. This set of SNRs may be initially obtained by performing theprocess shown in FIG. 4 for the MMSE-SC receiver, and may include SNRsthat exceed γ_(set).

[0149] Initially, the specific detection order corresponding to the setof post-detection SNRs is obtained (step 710). This detection order maybe represented as D={d₁, d₂, . . . d_(N) _(S) }, where d_(k) is theindex of the data stream recovered at stage k of the MMSE-SC receiver.The variable k used to denote the stage number is initialized to that ofthe last recovered data stream (i.e., k=N_(S)) and the index i of thedata stream x_(i) detected at stage k is set as i=d_(k) (step 712).

[0150] A determination is first made whether or not the post-detectionSNR, γ_(post)(i), for data stream x_(i) is greater than γ_(set) (step714). Alternatively, the power adjustment may be made only ifγ_(post)(i) is greater than γ_(set) by some delta amount. If the answeris no, then the transmit power for this data stream is not adjusted(i.e., {circumflex over (P)}_(i)=P_(i)) and the process proceeds to step720. Otherwise, the new transmit power, {circumflex over (P)}_(i), to beused for data stream x_(i) to achieve γ_(post)(i)=γ_(set) is determinedas shown in equation (23) (step 716).

[0151] A determination is then made whether or not all data streams havebeen considered (step 720). If the answer is yes, then the processterminates. Otherwise, the variable k is decremented and the data streamindex i is set as i=d_(k) (step 722), and the next prior stage isevaluated.

[0152] At any given stage k, a decrease in the transmit power for anylater-recovered data stream may increase the post-detection SNR of thedata stream recovered in this stage to be higher than γ_(set). Thus, adetermination is made whether or not there has been a transmit poweradjustment for any data stream recovered subsequent to stage k (step730). If the answer is no, then the process returns to step 714 toevaluate the data stream for the current stage k. Otherwise, if therehas been a power adjustment, then the MMSE spatial receiver processingis performed for stage k on the received symbol stream to obtain thepost-detection SNR for the data stream detected at stage k (step 732).This may be achieved by first determining the data streams that have notyet been recovered at stage k, which are denoted as D_(k)={d_(k), . . .d_(N) _(T) }. The transmit power originally used for the data streamdetected at stage k is then used together with the transmit powers ofthe data streams detected after stage k (at least one of which haschanged) to determine the post-detection SNR for the data streamdetected at stage k. In performing the MMSE-SC processing in reverseorder, the composite channel matrix increases for each stage and becomesthe original dimension of N_(R)×N_(T) for the first stage.

[0153] The result of the power adjustment in FIG. 7 is a set of transmitpowers, {{circumflex over (P)}_(i)}, for iεD, to be used for the datastreams. This set includes transmit powers that have been adjusted toachieve γ_(set). The total power saved for the new transmit powers maybe determined based on equation (15).

[0154] Another property of the MMSE-SC receiver is that detection orderhas no effect on spectral efficiency when there is no upper limit onpost-detection SNRs (i.e., γ_(set) does not exist). For the MMSE-SCreceiver, varying the detection order will produce differentpost-detection SNRs for the detected data streams, but the overallspectral efficiency for all data streams will remain the same. However,if there is an upper limit on post-detection SNRs and power control isemployed, then different detection orders may be associated withdifferent overall spectral efficiencies. In this case, a number ofdifferent detection orders may be evaluated to determine the one thatprovides the best spectral efficiency among the ones evaluated.Alternatively, an exhaustive search may be performed over all possibledetection orders to determine the specific detection order that achievesthe highest spectral efficiency.

[0155] The process shown in FIG. 5 may also be used to maximize spectralefficiency while minimizing the total required transmit power for theMMSE-SC receiver. Again, a list of detection orders to be evaluated maybe initially determined (step 512).

[0156] For each detection order to be evaluated, the received symbolstreams are initially processed using the MMSE-SC technique and based onthat detection order to obtain a set of post-detection SNRs for thedetected data streams (step 520). Each SNR in the set that is greaterthan γ_(set) is then adjusted to γ_(set) (step 522), and the transmitpower is thereafter adjusted accordingly to achieve the adjusted SNR.Because the post-detection SNR of a given data stream may be a functionof the transmit powers of the other data streams when using MMSEprocessing, an adjustment in the transmit power of one data stream maythen cause the post-detection SNRs of the other data streams to change.However, for the MMSE-SC technique, a change in the transmit power ofone data stream may only affect the post-detection SNR of a data streamthat has been detected earlier. This behavior may be taken into accountby using the process shown in FIG. 7 to perform the SNR adjustment.However, these changes in SNRs typically have a marginal effect on theoverall spectral efficiency and may be ignored. In any case, thespectral efficiency for each detection order is determined (step 524).

[0157] All detection orders in the list may be evaluated, one at a time,and the set of post-detection SNRs corresponding to the specificdetection order that yields the highest spectral efficiency, ρ_(max), issaved (step 528). The transmit powers needed to achieve the set ofadjusted post-detection SNRs corresponding to ρ_(max) are thendetermined (step 534), for example, using the process shown in FIG. 7.

[0158] The power control described herein may be implemented in variousmanners. In one implementation, a pilot is transmitted along with eachdata stream to allow the receiver to estimate the post-detection SNR ofthe data stream. The pilot may be transmitted at the peak transmit powerallowed for the data stream (i.e., P_(i)=P_(peak)). At the receiver, thereceived symbol streams are processed and the post-detection SNRs of thedetected data streams reflect the SNRs that would have been achieved ifthe peak transmit powers are used for the data streams. Power control isthen performed as described above to determine the minimum transmitpowers needed to achieve γ_(set) for the detected data streams at thereceiver. The power adjustments for the data streams would then beindicative of the amount of back-off from the peak transmit power.

[0159] In another implementation, the post-detection SNRs of thedetected data streams are reflective of the transmit powers actuallyused for the data streams. The power adjustments for the data streamswould then be indicative of the difference (or delta) from the currenttransmit powers.

Power Control for Discrete Data Rates

[0160] In the above description, it is assumed that spectral efficiencyis a continuous function of post-detection SNR, as shown in equation (5)and plot 212 in FIG. 2. Furthermore, the system described above allowsthe spectral efficiency to be any real value that does not exceed theρ_(set). A typical communication system, however, may only support a setof discrete data rates for each data stream. The data rate sets may ormay not be the same for all data streams. However, for simplicity, onedata rate set is assumed to be used for all data streams.

[0161]FIG. 8 shows a plot of spectral efficiency versus post-detectionSNR for a communication system that supports a set of discrete datarates. This set of data rates may be converted to a set of discretespectral efficiencies and is further associated with a set of discretepost-detection SNRs needed to achieve the target FER for a given datastream.

[0162] In FIG. 8, the discrete spectral efficiencies are labeled asρ_(set) (r) on the vertical axis, where r is used to enumerate throughthe R discrete data rates (i.e., 1≦r≦R). The spectral efficiencyfunction for this system is shown by plot 822 (the thick solid line).The highest spectral efficiency is ρ_(set) (1) and corresponds toγ_(set) (1). The discrete operating points at ((γ_(set)(r), ρ_(set)(r)),for 1≦r≦R, correspond to the minimum post-detection SNRs necessary toachieve the corresponding spectral efficiencies, and are shown by thesolid circles 824.

[0163] For a communication system with the spectral efficiency functionshown in FIG. 8, an increase in post-detection SNR may not offer animprovement in spectral efficiency. Therefore, utilizing more transmitpower than necessary to achieve the target FER at the operating spectralefficiency would result in an ineffective use of the additional transmitpower. Even though the excess transmit power may result in a lower FER,this improvement in FER may not be considered substantial since thetarget FER has already been achieved.

[0164] The power control techniques described above may also be used forsystems that support discrete data rates. The objective of the powercontrol is then to determine the transmit power for each data streamthat corresponds to the minimum SNR necessary to achieve the operatingspectral efficiency. New transmit powers may be determined for all datastreams that are not operating at the discrete γ_(set)(r) points.

[0165]FIG. 8 also shows an example whereby the initial operating pointsof three data streams, shown by dashed lines 826 a through 826 c, do notlie on the discrete operating points. The transmit power for each ofthese data streams may be reduced by a backed-off amount, BO(i), foriεD, so that the adjusted post-detection SNR lies on top of γ_(set)(r)for the discrete operating point. This then results in the data streamoperating at a lower transmit power without incurring a loss in spectralefficiency. As shown in FIG. 8, the post-detection SNR for data streamx_(i) may be backed off by BO(1), to achieve γ_(set)(1) required forspectral efficiency ρ_(set)(1) the post-detection SNR for data stream x₂may be backed off by BO(2), to achieve γ_(set)(3) required for spectralefficiency ρ_(set)(3), and the post-detection SNR for data stream x₃ maybe backed off by BO(3), to achieve γ_(set)(4) required for spectralefficiency ρ_(set)(4).

[0166] For the CCMI and CCMI-SC receivers, since the data streams aredecoupled at the output of these receivers, the transmit power of eachdata stream may be adjusted by the respective backed-off amount, BO(i),without affecting the post-detection SNRs of the other data streams.

[0167] For the MMSE receiver without successive cancellation, thepost-detection SNR of each data stream may be a function of the transmitpowers on all data streams, as noted above. This coupling may not allowall of the post-detection SNRs to be adjusted to lie exactly on top ofthe ideal operating points. In this case, the post-detection SNRs may beadjusted such that they exceed γ_(set)(r) by the smallest amountpossible. Again, a number of possible adjustments may be evaluated todetermine the best set of backed-off amounts.

[0168] For the MMSE-SC receiver, the post-detection SNRs of the datastreams may be adjusted in reverse detection order, as described above.The post-detection SNR of each data stream may then be adjusted by thebacked-off amount, BO(i), to achieve the discrete operating point,except for possibly the first data stream to be recovered.

Power Control for Specified Spectral Efficiency

[0169] The techniques described above may be used to achieve the maximumspectral efficiency for a given total transmit power, P_(tot). For aMIMO system that transmits using partial CSI, the optimization dependson the specific spatial receiver processing technique used at thereceiver as well as the achieved spectral efficiency of the coding andmodulation schemes available to both the transmitter and receiver.

[0170] The techniques described above may also be adapted to determinethe minimum amount of transmit power needed to achieve a specifiedspectral efficiency. For a MIMO system, instead of maximizing spectralefficiency, it may be possible for the system to be operated in a mannerwhereby the data rate or spectral efficiency of each user is controlledinstead of the transmit power. In this case, the system may specify aparticular data rate and an objective of the transmitter is then toachieve this specified data rate using the minimum amount of transmitpower. Again, the optimization depends on the specific spatial receiverprocessing technique used at the receiver as well as the performance ofthe system's coding and modulation schemes.

[0171] A specific scheme for determining the minimum amount of transmitpower required to achieve a specified spectral efficiency for a MIMOsystem utilizing partial CSI may be implemented as follows. For thisMIMO system, it is assumed that the transmitter employs N_(T) transmitantennas, each of which is capable of transmitting at up to a maximumtransmit power of P_(max). The total transmit power for all N_(T)transmit antennas is then P_(tot)=N_(T)*P_(max).

[0172] For this scheme, the set of transmit antennas that achieves themaximum spectral efficiency is initially determined based on theassumption that the peak transmit power, P_(max), is used for eachantenna. This set is denoted as the “optimal” set O. The spectralefficiency achieved by a given transmit antenna is dependent on thepost-detection SNR achieved by that antenna, which in turn is dependenton the specific receiver processing technique used at the receiver. Fora receiver processing technique that employs successive interferencecancellation, different detection orders may result in differentpost-detection SNRs for the transmit antennas. In that case, differentdetection orders may be evaluated to determine the set of transmitantennas that achieves the maximum spectral efficiency. Since the datastream on each transmit antenna acts as interference to the data streamson the other transmit antennas, the optimal set O may include less thanN_(T) transmit antennas if successive interference cancellation is notused, and typically includes all N_(T) transmit antennas if successiveinterference cancellation is used. Thus, the optimal set O may includeall N_(T) transmit antennas or only a subset of these antennas.

[0173] In an embodiment, the specified spectral efficiency is achievedby utilizing the minimum number of transmit antennas. For thisembodiment, the post-detection SNRs of the transmit antennas in set Oare first ranked in order from the highest to the lowest post-detectionSNR. From the ranked transmit antennas in set O, the minimum number oftransmit antennas, N_(req), needed to achieve the specified spectralefficiency is then determined. This may be achieved by selecting onetransmit antenna in set O at a time, starting with the best one havingthe highest post-detection SNR, and maintaining a running total of thespectral efficiencies of all selected transmit antennas. The set oftransmit antennas associated with an aggregate spectral efficiency thatis greater than or equal to the specified spectral efficiency is thendenoted as the required set R. Set R includes N_(req) transmit antennas,where N_(req)≦N_(T).

[0174] For the N_(req) transmit antennas in set R, the minimum amount oftransmit power required to achieve the specified spectral efficiency isthen determined. In an embodiment, the same back-off is applieduniformly to all N_(req) transmit antennas and the same amount oftransmit power is used for all N_(req) transmit antennas. This back-offmay be determined in an iterative manner by adjusting the transmitpowers for the N_(req) transmit antennas either up or down until thespecified spectral efficiency is achieved with the minimum amount oftransmit power. For a system that transmits data using a set of discretedata rates, different transmit powers may be used for the N_(req)transmit antennas, which may be determined as described above.

[0175] Alternatively, instead of achieving the specified spectralefficiency with the minimum number of transmit antennas as describedabove, more than N_(req) transmit antennas may be selected for use, andthe transmit power for each selected transmit antenna may be adjustedlower. Other schemes for determining the minimum amount of transmitpower to achieve the specified spectral efficiency may also beimplemented, and this is within the scope of the invention.

[0176] The determination of (1) the particular set of transmit antennasto use for data transmission and (2) the amount of transmit power to usefor each selected transmit antenna may be made at either the transmitteror receiver. If the determination is made at the receiver, then thetransmitter may be provided with control information indicative of theselected transmit antennas and their transmit powers to achieve thespecified spectral efficiency.

[0177] Since the link condition may change over time, the transmit powerto be used for the selected transmit antennas may be adjustedcorrespondingly to achieve the spectral efficiency in the presence ofchanging link condition. The post-detection SNRs of the data streamstransmitted on the selected transmit antennas may be determined based ona particular (e.g., CCMI, CCMI-SC, MMSE, or MMSE-SC) spatial receiverprocessing technique. Each of the post-detection SNRs may be greater orless than the setpoint, γ_(set)(i), needed to achieve the spectralefficiency designated for that transmit antenna. The transmit power foreach selected transmit antenna may then be adjusted either up or downsuch that the adjusted post-detection SNR is at or near the setpoint,γ_(set)(i). As noted above, for the MMSE receiver without successivecancellation, it may not be possible to set the post-detection SNRsexactly at the setpoints for all selected transmit antennas, in whichcase the adjustment may be made such that all selected transmit antennasachieve or exceed their setpoints while minimizing the amount of excesstransmit power. The power adjustment may also be performed in theaggregate for all selected transmit antennas.

[0178] The receiver may provide power control information to thetransmitter to allow the transmitter to adjust the transmit powers forthe selected transmit antennas. For example, the receiver may provide apower control bit for each selected transmit antenna or one powercontrol bit for all selected transmit antenna. Each power control bitmay indicate an adjustment of the transmit power either up or down bysome predetermined amount. Other power control mechanisms may also beemployed, and this is within the scope of the invention.

[0179] Power allocation for a MIMO system is also described in U.S.patent application Ser. No. [Attorney Docket No. 020038], entitled“Reallocation of Excess Power for Full Channel-State Information (CSI)Multiple-Input, Multiple-Output (MIMO) System,” filed Jan. 23, 2002,assigned to the assignee of the present application and incorporatedherein by reference.

Receiver

[0180]FIG. 9A is a block diagram of a RX MIMO/data processor 160 acapable of implementing the successive cancellation receiver processingtechnique. The transmitted signals from N_(T) transmit antennas arereceived by each of N_(R) antennas 152 a through 152 r and routed to arespective receiver 154. Each receiver 154 processes a respectivereceived signal and provides a corresponding received symbol stream toRX MIMO/data processor 160 a.

[0181] In the embodiment shown in FIG. 9A, RX MIMO/data processor 160 aincludes a number of successive (i.e., cascaded) receiver processingstages 910, one stage for each of the transmitted data streams to berecovered. Each receiver processing stage 910 (except for the last stage910 n) includes a spatial processor 920, an RX data processor 930, andan interference canceller 940, and the last stage 910 n includes onlyspatial processor 920 n and RX data processor 930 n.

[0182] For the first receiver processing stage 910 a, spatial processor920 a receives and processes the N_(R) received symbol streams (denotedas the vector y) from receivers 154 a through 154 r based on aparticular (e.g., CCMI or MMSE) receiver processing technique to provideN_(T) detected data streams (denoted as the vector {circumflex over(x)}¹). One of the detected data streams is selected (e.g., the firststream in the detection order D={d₁, d₂, . . . d_(N) _(T) }) andprovided to RX data processor 930 a. Processor 930 a further processes(e.g., demodulates, deinterleaves, and decodes) the selected detecteddata stream, {circumflex over (x)}_(i), where i=d₁ for the first stage,to provide a decoded data stream. Spatial processors 920 further provideCSI for the detected data streams, which may be in the form of thepost-detection SNRs described above.

[0183] For each of the second through last stages 910 b through 910 n,the spatial processor for that stage receives and processes the N_(R)modified symbol streams from the interference canceller in the precedingstage to derive the detected data streams for the stage. Again, one ofthe detected data streams is selected and processed by the RX dataprocessor to provide a decoded data stream for that stage.

[0184] For the first receiver processing stage 910 a, interferencecanceller 940 a receives the N_(R) received symbol streams fromreceivers 154 (denoted as the vector y¹). And for each of the secondthrough second-to-last stages, the interference canceller in that stagereceives the N_(R) modified symbol streams from the interferencecanceller in the preceding stage. Each interference canceller alsoreceives the decoded data stream from the RX data processor within thesame stage, and performs the processing (e.g., encoding, interleaving,modulation, channel response, and so on) to derive N_(R) remodulatedsymbol streams (denoted as the vector i) that are estimates of theinterference components due to the decoded data stream. The remodulatedsymbol streams are then subtracted from that stage's input symbolstreams to derive N_(R) modified symbol streams that include all but thesubtracted (i.e., cancelled) interference components. The N_(R) modifiedsymbol streams are then provided to the next stage.

[0185]FIG. 9B is a block diagram of a RX MIMO/data processor 160 b thatdoes not implement the successive cancellation receiver processingtechnique. The received symbol streams (denoted as the vector y) areprovided to spatial processor 920 and processed based on a particularspatial receiver processing technique to provide the detected datastreams (denoted as the vector {circumflex over (x)}). RX data processor930 then receives and processes the detected data streams to provide thedecoded data streams. Spatial processor 920 further provides CSI for thedetected data streams.

[0186]FIG. 10A is a block diagram of an embodiment of a spatialprocessor 920 x, which implements the CCMI technique. Spatial processor920 x may be used for each of spatial processors 920 a through 920 n inFIG. 9A and for spatial processors 920 in FIG. 9B. Within spatialprocessor 920 x, the received or modified symbol streams (denoted as thevector y) are initially filtered by a match filter 1012, whichpre-multiplies the vector y with the conjugate-transpose compositechannel matrix C^(H), as shown above in equation (7). A multiplier 1014further pre-multiplies the filtered vector with the inverse squarematrix R⁻¹ to form an estimate x of the transmitted vector x, as shownabove in equation (10).

[0187] The vector {circumflex over (x)} is provided to a channelestimator 1018 that estimates the channel response matrix H. In general,the matrix H may be estimated based on symbols corresponding to pilotdata or traffic data or both. Channel estimator 1018 then multiplies thechannel coefficient matrix H with the diagonal matrix, A, to obtain thecomposite channel matrix, C. A matrix processor 1020 then derives thecomposite channel correlation matrix R according to R=C^(H)C, as shownin equation (8). Channel estimator 1018 and matrix processor 1020provide the matrices C^(H) and R⁻¹, respectively, to match filter 1012and multiplier 1014.

[0188] Spatial processor 920 x provides one or more detected datastreams to RX data processor 930, which further processes (e.g.,demodulates, de-interleaves, and decodes) each detected data stream toprovide a corresponding decoded data stream.

[0189] A CSI processor 1016 determines the CSI for the detected datastreams, which may be in the form of the post-detection SNRs determinedas shown in equation (12). The CSI may be used to determine the transmitpower for the data streams.

[0190]FIG. 10B shows an embodiment of a spatial processor 920 y, whichimplements the MMSE technique. Similar to the CCMI technique, thematrices H and Λ_(n) may first be estimated based on the pilot and/ortraffic data. The matrices M and D_(v) ⁻¹ are then determined accordingto equation (18).

[0191] Within spatial processor 920 y, a multiplier 1022 initiallypre-multiplies the received or modified symbol streams (denoted as thevector y) with the matrix M to obtain an initial estimate of thetransmitted vector x, as shown in equation (18). A multiplier 1024further pre-multiplies the initial estimate with the diagonal matrixD_(v) ⁻¹ to form an unbiased estimate {circumflex over (x)} of thetransmitted vector x, as also shown in equation (18). The unbiasedestimate i corresponds to the detected data streams. The unbiasedestimate {circumflex over (x)} is further provided to an adaptiveprocessor 1026, which derives the matrices M and D_(v) ⁻¹ based onequation (18).

[0192] Spatial processor 920 y provides one or more detected datastreams to RX data processor 930 for further processing. CSI processor1016 determines CSI for the detected data streams, which again may be inthe form of the post-detection SNRs.

[0193] The CCMI, CCMI-SC, MMSE, and MMSE-SC receivers are described infurther detail in the aforementioned U.S. patent application Ser. Nos.09/993,087, 09/854,235, 09/826,481, and 09/956,449. In FIGS. 9A and 9B,each spatial processor 920 may be replaced with a space-time processor,which may implement the DFE, MMSE-LE, or MLSE, for a dispersive channelwithin frequency selective fading.

[0194] The power control may be performed by both the transmitter andreceiver systems. In an embodiment, the receiver system performs thespatial or space-time receiver processing on the received symbol streamsto obtain the detected data streams, estimates the post-detection SNRsof the detected data streams, determines the power adjustment for eachdetected data stream, and provides information indicative of which datastream requires power adjustment. In one embodiment, the receiver systemalso provides the power adjustment amount for each data stream thatneeds adjusting. In another embodiment, the power adjustment amount ispredetermined or fixed (e.g., 0.5 dB) and need not be reported.

[0195] Referring back to FIG. 1, at receiver system 150, controller 170may receive the post-detection SNRs and determine the power adjustment.Controller 170 may then provide the power control information andpossibly other information needed by the transmitter system to properlyprocess and transmit the data streams, which are collectively referredto as partial CSI. The partial CSI may comprise the post-detection SNRs,the data rates and coding and modulation schemes to be used for the datastreams, the power adjustments, and so on, or any combination thereof.The partial CSI is then processed by TX data processor 178, modulated bymodulator 180, conditioned by transmitters 154, and transmitted viaantennas 152.

[0196] At transmitter system 110, the transmitted signals from receiversystem 150 are received by antennas 124. The received signals are thenconditioned by receiver 122, demodulated by demodulator 140, and furtherprocessed by RX data processor 142 to recover the reported CSI, which isprovided to controller 130. Controller 130 then provides variouscontrols used to process (e.g., code and modulate) the data streams andadjust the transmit powers for these data streams.

[0197] The techniques described herein for controlling transmit powermay be used for various multi-channel communication systems, includingMIMO systems, OFDM systems, MIMO-OFDM systems, and so on. Thesetechniques may be advantageously used for systems having a particularmaximum allowed spectral efficiency, ρ_(set), (as illustrated in FIG. 2)and for systems supporting one or more sets of discrete data rates forthe data streams (as illustrated in FIG. 8).

[0198] The techniques described herein may also be used to controltransmit power for each data stream, which may be transmitted on one ormore transmission channels. Each data stream may be associated with aparticular data rate and a particular coding and modulation scheme. Fora multiple-access communication system, each data stream may beassociated with a different receiver.

[0199] For clarity, the power control is specifically described for theCCMI, CCMI-SC, MMSE, and MMSE-SC receiver processing techniques. Thepower control techniques described herein may also be used for otherreceiver processing techniques, and this is within the scope of theinvention. For example, these power control techniques may be used inconjunction with space-time receiver processing techniques.

[0200] The power control techniques described herein may be implementedby various means. For example, these techniques may be implemented inhardware, software, or a combination thereof. For a hardwareimplementation, the elements used to control transmit power for the datastreams may be implemented within one or more application specificintegrated circuits (ASICs), digital signal processors (DSPs), digitalsignal processing devices (DSPDs), programmable logic devices (PLDs),field programmable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described herein, or a combination thereof.

[0201] For a software implementation, the power control may beimplemented with modules (e.g., procedures, functions, and so on) thatperform the functions described herein. The software codes may be storedin a memory unit (e.g., memory 132 and/or 172 in FIG. 1) and executed bya processor (e.g., controller 130 and/or 170). The memory unit may beimplemented within the processor or external to the processor, in whichcase it can be communicatively coupled to the processor via variousmeans as is known in the art.

[0202] Headings are included herein for reference and to aid in locatingcertain sections. These headings are not intended to limit the scope ofthe concepts described therein under, and these concepts may haveapplicability in other sections throughout the entire specification.

[0203] The previous description of the disclosed embodiments is providedto enable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thespirit or scope of the invention. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

What is claimed is:
 1. A method for controlling transmit power for aplurality of data streams in a wireless multi-channel communicationsystem, comprising: processing a plurality of received symbol streams inaccordance with a particular receiver processing technique to provide aplurality of detected data streams; estimatingsignal-to-noise-and-interference ratios (SNRs) of the plurality ofdetected data streams; identifying each SNR that exceeds a setpoint; anddetermining an adjusted transmit power for each detected data streamassociated with an SNR exceeding the setpoint.
 2. The method of claim 1,wherein the received symbol streams are processed in accordance with asuccessive interference cancellation receiver processing technique. 3.The method of claim 2, wherein the received symbol streams are furtherprocessed based on a particular detection order to provide the pluralityof detected data streams.
 4. The method of claim 2, wherein the receivedsymbol streams are further processed based on a specific detection, fromminimum SNR to maximum SNR.
 5. The method of claim 3, wherein theplurality of detected data streams are decoupled by the successiveinterference cancellation receiver processing.
 6. The method of claim 3,wherein the plurality of detected data streams are not decoupled by thesuccessive interference cancellation receiver processing.
 7. The methodof claim 6, wherein the adjusted transmit powers for the plurality ofdetected data streams are determined in reverse detection order.
 8. Themethod of claim 2, further comprising: determining a list of detectionorders to be evaluated; evaluating each detection order in the list byprocessing the plurality of received symbol streams in accordance withthe successive interference cancellation receiver processing techniqueand based on the detection order to provide a plurality of detected datastreams, estimating the SNRs of the plurality of detected data streams,deriving adjusted SNRs for the plurality of detected data streams byadjusting each SNR that exceeds the setpoint to be equal to thesetpoint, and determining spectral efficiency for the detected datastreams based on the adjusted SNRs, and wherein the adjusted transmitpowers for the detected data streams are determined for a particulardetection order selected based on the spectral efficiencies determinedfor the detection orders in the list.
 9. The method of claim 8, whereinthe detection order associated with a highest spectral efficiency isselected.
 10. The method of claim 1, wherein the plurality of detecteddata streams are decoupled by the receiver processing.
 11. The method ofclaim 1, wherein the plurality of detected data streams are notdecoupled by the receiver processing.
 12. The method of claim 11,further comprising: repeating the processing, estimating, identifying,and determining for one or more iterations.
 13. The method of claim 1,wherein the SNR of each detected data stream is achieved based on a peaktransmit power for the data stream.
 14. The method of claim 1, whereinthe received symbol streams are processed in accordance with a channelcorrelation matrix inversion (CCMI) spatial receiver processingtechnique.
 15. The method of claim 1, wherein the received symbolstreams are processed in accordance with a channel correlation matrixinversion with successive interference cancellation (CCMI-SC) receiverprocessing technique.
 16. The method of claim 1, wherein the receivedsymbol streams are processed in accordance with a minimum mean squareerror (MMSE) spatial receiver processing technique.
 17. The method ofclaim 1, wherein the received symbol streams are processed in accordancewith a minimum mean square error with successive interferencecancellation (MMSE-SC) receiver processing technique.
 18. The method ofclaim 1, wherein the received symbol streams are processed in accordancewith a space-time receiver processing technique.
 19. The method of claim1, wherein the multi-channel communication system is a multiple-inputmultiple-output (MIMO) communication system.
 20. The method of claim 1,wherein the multi-channel communication system is an orthogonalfrequency division multiplexing (OFDM) communication system.
 21. Themethod of claim 1, wherein the multi-channel communication system is amultiple-input multiple-output (MIMO) communication system that utilizesorthogonal frequency division multiplexing (OFDM).
 22. A method forcontrolling transmit power for a plurality of data streams in amultiple-input multiple-output (MIMO) communication system, comprising:processing a plurality of received symbol streams in accordance with achannel correlation matrix inversion (CCMI) or a minimum mean squareerror (MMSE) spatial receiver processing technique to provide aplurality of detected data streams; estimatingsignal-to-noise-and-interference ratios (SNRs) of the plurality ofdetected data streams; identifying each SNR that exceeds a setpoint; anddetermining an adjusted transmit power for each detected data streamassociated with an SNR exceeding the setpoint.
 23. A method forcontrolling transmit power for a plurality of data streams in amultiple-input multiple-output (MIMO) communication system, comprising:processing a plurality of received symbol streams in accordance with achannel correlation matrix inversion with successive interferencecancellation (CCMI-SC) or a minimum mean square error with successiveinterference cancellation (MMSE-SC) receiver processing technique andbased on a particular detection order to provide a plurality of detecteddata streams; estimating signal-to-noise-and-interference ratios (SNRs)of the plurality of detected data streams; identifying each SNR thatexceeds a setpoint; and determining an adjusted transmit power for eachdetected data stream associated with an SNR exceeding the setpoint. 24.A method for controlling transmit power for a plurality of data streamsin a multiple-input multiple-output (MIMO) communication system,comprising: processing a plurality of received symbol streams inaccordance with a particular receiver processing technique to provide aplurality of detected data streams; estimatingsignal-to-noise-and-interference ratios (SNRs) of the plurality ofdetected data streams; identifying a set of one or more detected datastreams each associated with an SNR that exceeds an associated operatingpoint; and determining an adjusted transmit power for each detected datastream in the set to move the SNR toward the associated operating point.25. The method of claim 24, wherein each data stream is transmitted asone of a plurality of possible discrete data rates, and wherein eachdiscrete data rate is associated with a respective operating point. 26.The method of claim 25, wherein each operating point corresponds to anSNR needed to achieve a particular performance level for the associateddiscrete data rate.
 27. The method of claim 24, wherein the plurality ofdetected data streams are not decoupled by the receiver processing, themethod further comprising: repeating the processing, estimating,identifying, and determining for a plurality of iterations.
 28. Themethod of claim 24, wherein the plurality of received symbol streams areprocessed in accordance with a successive interference cancellationreceiver processing technique.
 29. The method of claim 28, wherein theplurality of detected data streams are not decoupled by the receiverprocessing, and wherein the adjusted transmit powers for the pluralityof detected data streams are determined in reverse detection order. 30.A method for determining an amount of transmit power required to achievea specified spectral efficiency in a wireless multi-channelcommunication system, comprising: determining a first set oftransmission channels selectable for use for data transmission;estimating performance of each of transmission channel in the first set,wherein each transmission channel is associated with a particularspectral efficiency; determining a second set of transmission channelsto be used for data transmission, wherein the second set include aminimum number of transmission channels from the first set with anaggregate spectral efficiency that meets the specified spectralefficiency; and determining transmit power for each of the transmissionchannels in the second set to reduce overall transmit power whileachieving the specified spectral efficiency.
 31. The method of claim 30,wherein each transmission channel in the first set corresponds to arespective transmit antenna.
 32. The method of claim 30, wherein thetransmission channels in the first set achieves a maximum aggregatespectral efficiency among all transmission channels available for use.33. The method of claim 30, wherein the particular spectral efficiencyassociated with each transmission channel in the first set is determinedbased on peak transmit power being used for the transmission channel.34. The method of claim 30, wherein the transmission channels in thesecond set have best performance among the transmission channels in thefirst set.
 35. The method of claim 30, further comprising: ranking thetransmission channels in the first set; and selecting the transmissionchannels in the first set, one at a time, until the aggregate spectralefficiency of the selected transmission channels is equal to or greaterthan the specified spectral efficiency.
 36. The method of claim 30,wherein transmit powers for the transmission channels in the second setare adjusted to be approximately equal.
 37. The method of claim 30,further comprising: receiving indication of changes to link conditions;and adjusting the transmit powers of the transmission channels in thesecond set to achieve the spectral efficiency with the changes in thelink conditions.
 38. A method for controlling transmit power for aplurality of data streams transmitted on a plurality of transmissionchannels in a wireless multi-channel communication system, comprising:processing a plurality of received symbol streams in accordance with aparticular receiver processing technique to provide a plurality ofdetected data streams; estimating signal-to-noise-and-interferenceratios (SNRs) of the plurality of detected data streams; determining adifference between the SNR of each data stream and a setpoint associatedwith the data stream; and determining an adjusted transmit power foreach detected data stream based on the determined difference between theSNR and the setpoint.
 39. The method of claim 38, wherein the pluralityof detected data streams achieve a specified spectral efficiency. 40.The method of claim 38, wherein the multi-channel communication systemis a multiple-input multiple-output (MIMO) communication system.
 41. Amemory communicatively coupled to a digital signal processing device(DSPD) capable of interpreting digital information to: process aplurality of received symbol streams in accordance with a particularreceiver processing technique to provide a plurality of detected datastreams; estimate signal-to-noise-and-interference ratios (SNRs) of theplurality of detected data streams; identify each SNR that exceeds asetpoint; and determine an adjusted transmit power for each detecteddata stream associated with an SNR exceeding the setpoint.
 42. Acomputer program product for controlling transmit power for a pluralityof data streams in a wireless multi-channel communication system,comprising: code for processing a plurality of received symbol streamsin accordance with a particular receiver processing technique to providea plurality of detected data streams; code for estimatingsignal-to-noise-and-interference ratios (SNRs) of the plurality ofdetected data streams; code for identifying each SNR that exceeds asetpoint; code for determining an adjusted transmit power for eachdetected data stream associated with an SNR exceeding the setpoint; anda computer-usable medium for storing the codes
 43. An integrated circuitin a wireless communication system, comprising: means for processing aplurality of received symbol streams in accordance with a particularreceiver processing technique to provide a plurality of detected datastreams; means for estimating signal-to-noise-and-interference ratios(SNRs) of the plurality of detected data streams; means for identifyingeach SNR that exceeds a setpoint; and means for determining an adjustedtransmit power for each detected data stream associated with an SNRexceeding the setpoint.
 44. A receiver unit in a multi-channelcommunication system, comprising: a receive processor operative toprocess a plurality of received symbol streams in accordance with aparticular receiver processing technique to provide a plurality ofdetected data streams, and to estimate signal-to-noise-and-interferenceratios (SNRs) of the plurality of detected data streams; and acontroller operative to identify each SNR that exceeds a setpoint, andto determine an adjusted transmit power for each detected data streamassociated with an SNR exceeding the setpoint.
 45. The receiver unit ofclaim 44, wherein the receive processor is operative to process theplurality of received symbol streams in accordance with a successiveinterference cancellation receiver processing technique.
 46. Thereceiver unit of claim 44, wherein the controller is further operativeto provide channel-state information (CSI) comprising identities of datastreams with adjusted transmit powers.
 47. The receiver unit of claim46, further comprising: a transmit processor operative to process theCSI for transmission back to a transmitter unit.
 48. A terminalcomprising the receiver unit of claim
 44. 49. A base station comprisingthe receiver unit of claim
 44. 50. A receiver apparatus in amulti-channel communication system, comprising: means for processing aplurality of received symbol streams in accordance with a particularreceiver processing technique to provide a plurality of detected datastreams; means for estimating signal-to-noise-and-interference ratios(SNRs) of the plurality of detected data streams; means for identifyingeach SNR that exceeds a setpoint; and means for determining an adjustedtransmit power for each detected data stream associated with an SNRexceeding the setpoint.
 51. A transmitter unit in a wirelesscommunication system, comprising: a transmit (TX) data processoroperative to code a plurality of data streams based on one or morecoding and modulation schemes to provide a plurality of modulationsymbol streams, and to scale each modulation symbol stream based on arespective weight corresponding to an amount of transmit power to beused for the corresponding data stream; a plurality of transmittersoperative to process the plurality of scaled symbol streams to provide aplurality of modulated signals suitable for transmission over acommunication channel; and a controller operative to receivechannel-state information (CSI) indicative of power adjustments for oneor more data streams, wherein the power adjustments are derived byprocessing a plurality of received symbol streams in accordance with aparticular receiver processing technique to provide a plurality ofdetected data streams, estimating signal-to-noise-and-interferenceratios (SNRs) of the plurality of detected data streams, identifyingeach SNR that exceeds a setpoint, and determining power adjustment foreach detected data stream associated with an SNR exceeding the setpoint.52. A base station comprising the transmitter unit of claim 51.